The COVID-19 Situation Report is a data intensive report that tries to portray an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic. If you would like to add additional metrics to this report, please send a mail to the author at .

Date of Report

Numbers as on EOD

## [1] "2020-05-29"

COVID-19 Overall Stats (Worldwide)

Overall Confirmed Cases Count Worldwide

## [1] "5924275 (up from 5808946 yesterday: 1.99 % increase)"

Overall Deaths Worldwide

Please note that the deaths is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] "364867 (up from 360308 yesterday: 1.27 % increase)"

Overall Fatality Rate Worldwide in %

Please note that the fatality rate is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] 6.16



In- Depth Country Wise Stats (With Atleast 1000 COVID-19 Confirmations)

Overall Confirmed Cases and Deaths- Country Wise (With Fatality Rates)

Country_Region TotalConfirmed NewConfirmations CasesPercentIncrease TotalDeaths NewDeaths DeathsPercentIncrease FatalityRate
US 1746019 24266 1.41 102809 1193 1.17 5.89
Brazil 465166 26928 6.14 27878 1124 4.20 5.99
Russia 387623 8572 2.26 4374 232 5.60 1.13
United Kingdom 272607 2099 0.78 38243 324 0.85 14.03
Spain 238564 658 0.28 27121 2 0.01 11.37
Italy 232248 516 0.22 33229 87 0.26 14.31
France 186923 559 0.30 28717 52 0.18 15.36
Germany 182922 726 0.40 8504 34 0.40 4.65
India 173491 8105 4.90 4980 269 5.71 2.87
Turkey 162120 1141 0.71 4489 28 0.63 2.77
Iran 146668 2819 1.96 7677 50 0.66 5.23
Peru 141779 0 0.00 4099 0 0.00 2.89
Canada 90909 933 1.04 7063 81 1.16 7.77
Chile 90638 3695 4.25 944 54 6.07 1.04
Mexico 84627 3227 3.96 9415 371 4.10 11.13
China 84123 17 0.02 4638 0 0.00 5.51
Saudi Arabia 81766 1581 1.97 458 17 3.85 0.56
Pakistan 64028 2801 4.57 1317 57 4.52 2.06
Belgium 58061 212 0.37 9430 42 0.45 16.24
Qatar 52907 1993 3.91 36 3 9.09 0.07
Netherlands 46328 176 0.38 5950 28 0.47 12.84
Bangladesh 42844 2523 6.26 582 23 4.11 1.36
Belarus 40764 906 2.27 224 5 2.28 0.55
Ecuador 38571 100 0.26 3334 21 0.63 8.64
Sweden 36476 749 2.10 4350 84 1.97 11.93
Singapore 33860 611 1.84 23 0 0.00 0.07
United Arab Emirates 33170 638 1.96 260 2 0.78 0.78
Portugal 31946 350 1.11 1383 14 1.02 4.33
Switzerland 30828 32 0.10 1919 0 0.00 6.22
South Africa 29240 1837 6.70 611 34 5.89 2.09
Colombia 25406 1265 5.24 855 22 2.64 3.37
Indonesia 25216 678 2.76 1520 24 1.60 6.03
Kuwait 25184 1072 4.45 194 9 4.86 0.77
Ireland 24876 35 0.14 1645 6 0.37 6.61
Poland 23155 330 1.45 1051 13 1.25 4.54
Ukraine 22811 429 1.92 679 10 1.49 2.98
Egypt 22082 1289 6.20 879 34 4.02 3.98
Romania 18982 191 1.02 1248 13 1.05 6.57
Israel 16987 115 0.68 284 0 0.00 1.67
Japan 16673 75 0.45 887 6 0.68 5.32
Austria 16655 27 0.16 668 0 0.00 4.01
Philippines 16634 1046 6.71 942 21 2.28 5.66
Dominican Republic 16531 463 2.88 488 3 0.62 2.95
Argentina 15419 717 4.88 520 12 2.36 3.37
Afghanistan 13659 623 4.78 246 11 4.68 1.80
Panama 12531 400 3.30 326 6 1.88 2.60
Denmark 11793 81 0.69 568 0 0.00 4.82
Korea, South 11441 39 0.34 269 0 0.00 2.35
Serbia 11354 54 0.48 242 1 0.41 2.13
Bahrain 10449 397 3.95 15 0 0.00 0.14
Kazakhstan 9932 356 3.72 37 0 0.00 0.37
Oman 9820 811 9.00 40 0 0.00 0.41
Nigeria 9302 387 4.34 261 2 0.77 2.81
Czechia 9196 56 0.61 319 0 0.00 3.47
Algeria 9134 137 1.52 638 8 1.27 6.98
Bolivia 8731 344 4.10 300 7 2.39 3.44
Armenia 8676 460 5.60 120 7 6.19 1.38
Norway 8422 11 0.13 236 0 0.00 2.80
Moldova 7896 171 2.21 288 6 2.13 3.65
Malaysia 7732 103 1.35 115 0 0.00 1.49
Morocco 7714 71 0.93 202 0 0.00 2.62
Ghana 7616 313 4.29 34 0 0.00 0.45
Australia 7184 19 0.27 103 0 0.00 1.43
Finland 6776 33 0.49 314 1 0.32 4.63
Iraq 5873 416 7.62 185 6 3.35 3.15
Cameroon 5436 0 0.00 177 2 1.14 3.26
Azerbaijan 4989 230 4.83 58 2 3.57 1.16
Honduras 4752 0 0.00 196 0 0.00 4.12
Guatemala 4607 259 5.96 90 10 12.50 1.95
Sudan 4521 175 4.03 233 38 19.49 5.15
Luxembourg 4012 4 0.10 110 0 0.00 2.74
Hungary 3841 25 0.66 517 8 1.57 13.46
Tajikistan 3686 123 3.45 47 0 0.00 1.28
Guinea 3656 103 2.90 22 0 0.00 0.60
Uzbekistan 3468 24 0.70 14 0 0.00 0.40
Senegal 3429 81 2.42 41 2 5.13 1.20
Thailand 3076 11 0.36 57 0 0.00 1.85
Djibouti 2914 0 0.00 20 0 0.00 0.69
Greece 2909 3 0.10 175 0 0.00 6.02
Congo (Kinshasa) 2833 173 6.50 69 0 0.00 2.44
Cote d’Ivoire 2750 109 4.13 32 0 0.00 1.16
Gabon 2613 182 7.49 15 1 7.14 0.57
Bosnia and Herzegovina 2485 23 0.93 153 0 0.00 6.16
Bulgaria 2485 8 0.32 136 2 1.49 5.47
El Salvador 2278 84 3.83 42 3 7.69 1.84
Croatia 2245 0 0.00 103 1 0.98 4.59
North Macedonia 2129 52 2.50 126 5 4.13 5.92
Cuba 2005 22 1.11 82 0 0.00 4.09
Estonia 1859 8 0.43 67 1 1.52 3.60
Somalia 1828 0 0.00 72 0 0.00 3.94
Iceland 1805 0 0.00 10 0 0.00 0.55
Kenya 1745 127 7.85 62 4 6.90 3.55
Kyrgyzstan 1662 68 4.27 16 0 0.00 0.96
Lithuania 1662 6 0.36 68 0 0.00 4.09
Maldives 1591 78 5.16 5 0 0.00 0.31
Haiti 1584 264 20.00 35 1 2.94 2.21
Sri Lanka 1558 28 1.83 10 0 0.00 0.64
Slovakia 1520 0 0.00 28 0 0.00 1.84
New Zealand 1504 0 0.00 22 0 0.00 1.46
Slovenia 1473 0 0.00 108 0 0.00 7.33
Venezuela 1370 45 3.40 14 3 27.27 1.02
Equatorial Guinea 1306 263 25.22 12 0 0.00 0.92
Guinea-Bissau 1256 61 5.10 8 0 0.00 0.64
Mali 1226 32 2.68 73 1 1.39 5.95
Nepal 1212 170 16.31 6 1 20.00 0.50
Lebanon 1172 4 0.34 26 0 0.00 2.22
Albania 1099 23 2.14 33 0 0.00 3.00
Tunisia 1071 3 0.28 48 0 0.00 4.48
Latvia 1064 3 0.28 24 0 0.00 2.26
Zambia 1057 0 0.00 7 0 0.00 0.66
Kosovo 1048 0 0.00 30 0 0.00 2.86
Costa Rica 1022 22 2.20 10 0 0.00 0.98

In Depth USA Stats (State Wise Figures)

Confirmed Cases and Deaths- States of USA (With Fatality Rates)

State Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
New York 368284 1551 0.42 29646 117 0.40 8.05 18931.44 1523.94 1 in 53
New Jersey 158844 1659 1.06 11531 122 1.07 7.26 17883.43 1298.22 1 in 56
Illinois 117455 1622 1.40 5270 84 1.62 4.49 9268.99 415.88 1 in 108
California 106622 2809 2.71 4077 84 2.10 3.82 2698.46 103.18 1 in 371
Massachusetts 95512 617 0.65 6718 78 1.17 7.03 13743.72 966.69 1 in 73
Pennsylvania 74984 764 1.03 5464 91 1.69 7.29 5857.21 426.81 1 in 171
Texas 60901 506 0.84 1619 8 0.50 2.66 2100.33 55.84 1 in 476
Michigan 56621 607 1.08 5406 34 0.63 9.55 5669.55 541.31 1 in 176
Florida 54497 1212 2.27 2413 49 2.07 4.43 2537.37 112.35 1 in 394
Maryland 50988 1279 2.57 2466 38 1.57 4.84 8433.79 407.89 1 in 119
Georgia 45881 615 1.36 1987 14 0.71 4.33 4321.29 187.15 1 in 231
Virginia 42533 1132 2.73 1358 20 1.49 3.19 4983.06 159.10 1 in 201
Connecticut 41762 203 0.49 3868 42 1.10 9.26 11713.50 1084.91 1 in 85
Louisiana 38802 0 0.00 2767 26 0.95 7.13 8346.68 595.21 1 in 120
Ohio 34566 651 1.92 2131 33 1.57 6.17 2957.11 182.31 1 in 338
Indiana 33558 490 1.48 2110 42 2.03 6.29 4984.69 313.42 1 in 201
North Carolina 26885 1085 4.21 919 43 4.91 3.42 2563.39 87.62 1 in 390
Colorado 25598 491 1.96 1436 15 1.06 5.61 4445.07 249.36 1 in 225
Minnesota 23531 584 2.54 1006 29 2.97 4.28 4172.44 178.38 1 in 240
Tennessee 22063 384 1.77 361 5 1.40 1.64 3228.81 52.83 1 in 310
Washington 21071 307 1.48 1111 5 0.45 5.27 2767.08 145.90 1 in 361
Iowa 18957 371 2.00 524 18 3.56 2.76 6008.42 166.08 1 in 166
Arizona 18472 595 3.33 886 26 3.02 4.80 2425.77 116.35 1 in 412
Wisconsin 17707 733 4.32 568 18 3.27 3.21 3041.17 97.55 1 in 329
Alabama 17031 501 3.03 610 19 3.21 3.58 3473.46 124.41 1 in 288
Mississippi 14793 421 2.93 710 17 2.45 4.80 4970.52 238.56 1 in 201
Rhode Island 14635 141 0.97 693 16 2.36 4.74 13814.93 654.17 1 in 72
Nebraska 13648 399 3.01 164 1 0.61 1.20 7055.39 84.78 1 in 142
Missouri 13084 103 0.79 730 22 3.11 5.58 2131.84 118.94 1 in 469
South Carolina 11131 343 3.18 483 13 2.77 4.34 2161.90 93.81 1 in 463
Kansas 9662 291 3.11 215 1 0.47 2.23 3316.50 73.80 1 in 302
Kentucky 9464 279 3.04 418 9 2.20 4.42 2118.33 93.56 1 in 472
Utah 9264 343 3.84 107 1 0.94 1.16 2889.62 33.38 1 in 346
Delaware 9236 65 0.71 356 11 3.19 3.85 9484.84 365.59 1 in 105
District of Columbia 8538 46 0.54 460 7 1.55 5.39 12097.79 651.79 1 in 83
Nevada 8376 128 1.55 406 0 0.00 4.85 2719.34 131.81 1 in 368
New Mexico 7493 129 1.75 344 9 2.69 4.59 3573.49 164.06 1 in 280
Arkansas 6777 239 3.66 132 7 5.60 1.95 2245.66 43.74 1 in 445
Oklahoma 6338 65 1.04 329 4 1.23 5.19 1601.73 83.14 1 in 624
South Dakota 4866 73 1.52 59 5 9.26 1.21 5500.42 66.69 1 in 182
New Hampshire 4492 103 2.35 238 6 2.59 5.30 3303.64 175.04 1 in 303
Oregon 4131 45 1.10 151 0 0.00 3.66 979.44 35.80 1 in 1021
Puerto Rico 3647 161 4.62 132 1 0.76 3.62 1141.94 41.33 1 in 876
Idaho 2770 0 0.00 82 0 0.00 2.96 1545.70 45.76 1 in 647
North Dakota 2520 39 1.57 59 2 3.51 2.34 3306.82 77.42 1 in 302
Maine 2226 37 1.69 85 1 1.19 3.82 1655.99 63.23 1 in 604
West Virginia 1951 16 0.83 74 0 0.00 3.79 1091.68 41.41 1 in 916
Vermont 975 1 0.10 55 0 0.00 5.64 1562.53 88.14 1 in 640
Wyoming 891 15 1.71 15 0 0.00 1.68 1539.50 25.92 1 in 650
Hawaii 649 2 0.31 17 0 0.00 2.62 458.37 12.01 1 in 2182
Montana 493 8 1.65 17 0 0.00 3.45 461.27 15.91 1 in 2168
Alaska 429 5 1.18 10 0 0.00 2.33 586.43 13.67 1 in 1705

US Tested- Confirmed Funnel (All States)

State Level Figures

State Tested Confirmed ConfirmationRate TestsPerMillPopl
New York 1944130 368284 18.94 99936.97
New Jersey 716411 158844 22.17 80657.02
Illinois 851762 117455 13.79 67217.02
California 1835478 106622 5.81 46453.42
Massachusetts 571745 95512 16.71 82271.35
Pennsylvania 438309 74984 17.11 34237.57
Texas 893275 60901 6.82 30806.96
Michigan 521607 56621 10.86 52229.35
Florida 983239 54497 5.54 45779.45
Maryland 284518 50988 17.92 47061.37
Georgia 450271 45881 10.19 42408.69
Virginia 298377 42533 14.25 34957.10
Connecticut 241393 41762 17.30 67706.47
Louisiana 355027 38802 10.93 76369.70
Ohio 369890 34566 9.34 31644.01
Indiana 248713 33558 13.49 36943.69
North Carolina 391231 26885 6.87 37302.43
Colorado 168959 25598 15.15 29339.60
Minnesota 233873 23531 10.06 41469.55
Tennessee 421967 22063 5.23 61752.71
Washington 343091 21071 6.14 45055.26
Iowa 147320 18957 12.87 46693.10
Arizona 209813 18472 8.80 27552.98
Wisconsin 251295 17707 7.05 43159.79
Alabama 208883 17031 8.15 42601.49
Mississippi 166308 14793 8.89 55880.27
Rhode Island 146355 14635 10.00 138154.04
Nebraska 94803 13648 14.40 49008.79
Missouri 177850 13084 7.36 28977.94
South Carolina 188257 11131 5.91 36563.89
Kansas 94949 9662 10.18 32591.41
Kentucky 221274 9464 4.28 49527.80
Utah 205855 9264 4.50 64210.14
Delaware 57533 9236 16.05 59083.10
District of Columbia 43858 8538 19.47 62143.91
Nevada 134416 8376 6.23 43639.35
New Mexico 183544 7493 4.08 87534.08
Arkansas 119768 6777 5.66 39686.86
Oklahoma 187398 6338 3.38 47358.95
South Dakota 40682 4866 11.96 45986.08
New Hampshire 66862 4492 6.72 49173.68
Oregon 122681 4131 3.37 29086.93
Puerto Rico 3647 3647 100.00 1141.94
Idaho 44761 2770 6.19 24977.33
North Dakota 69453 2520 3.63 91138.25
Maine 45706 2226 4.87 34002.08
West Virginia 93377 1951 2.09 52249.20
Vermont 31885 975 3.06 51098.66
Wyoming 23269 891 3.83 40204.99
Hawaii 52824 649 1.23 37308.46
Montana 38529 493 1.28 36049.58
Alaska 49439 429 0.87 67581.63

In Depth India Stats (State Wise Figures)

Confirmed Cases and Deaths (States of India)

State Confirmed NewConfirmations CasesPercentIncrease Recovered RecoveryRate Active Deaths NewDeaths DeathsPercentIncrease FatalityRate
Maharashtra 62228 2682 4.50 26997 43.38 33133 2098 116 5.85 3.37
Tamil Nadu 20246 874 4.51 11313 55.88 8776 157 9 6.08 0.78
Delhi 17386 1105 6.79 7846 45.13 9142 398 82 25.95 2.29
Gujarat 15944 372 2.39 8611 54.01 6353 980 20 2.08 6.15
Rajasthan 8365 298 3.69 5244 62.69 2937 184 4 2.22 2.20
Madhya Pradesh 7645 192 2.58 4269 55.84 3042 334 13 4.05 4.37
Uttar Pradesh 7445 275 3.84 4410 59.23 2834 201 4 2.03 2.70
West Bengal 4813 277 6.11 1775 36.88 2736 302 7 2.37 6.27
State Unassigned 4673 0 0.00 0 0.00 4673 0 0 NaN 0.00
Bihar 3359 174 5.46 1209 35.99 2135 15 0 0.00 0.45
Andhra Pradesh 3330 85 2.62 2234 67.09 1036 60 1 1.69 1.80
Karnataka 2781 248 9.79 894 32.15 1837 48 1 2.13 1.73
Telangana 2425 169 7.49 1381 56.95 973 71 4 5.97 2.93
Punjab 2197 39 1.81 1949 88.71 206 42 2 5.00 1.91
Jammu and Kashmir 2164 128 6.29 875 40.43 1261 28 1 3.70 1.29
Odisha 1723 63 3.80 977 56.70 737 9 2 28.57 0.52
Haryana 1721 217 14.43 940 54.62 762 19 0 0.00 1.10
Kerala 1151 62 5.69 565 49.09 577 9 1 12.50 0.78
Assam 1058 177 20.09 126 11.91 925 4 0 0.00 0.38
Uttarakhand 716 216 43.20 102 14.25 607 4 0 0.00 0.56
Jharkhand 521 51 10.85 216 41.46 300 5 1 25.00 0.96
Chhattisgarh 415 17 4.27 100 24.10 314 1 1 Inf 0.24
Himachal Pradesh 295 14 4.98 83 28.14 203 6 0 0.00 2.03
Chandigarh 289 0 0.00 189 65.40 96 4 0 0.00 1.38
Tripura 254 10 4.10 167 65.75 87 0 0 NaN 0.00
Ladakh 74 0 0.00 43 58.11 31 0 0 NaN 0.00
Goa 69 0 0.00 41 59.42 28 0 0 NaN 0.00
Manipur 59 4 7.27 6 10.17 53 0 0 NaN 0.00
Puducherry 53 0 0.00 17 32.08 36 0 0 NaN 0.00
Andaman and Nicobar Islands 33 0 0.00 33 100.00 0 0 0 NaN 0.00
Meghalaya 27 6 28.57 12 44.44 14 1 0 0.00 3.70
Nagaland 25 7 38.89 0 0.00 25 0 0 NaN 0.00
Arunachal Pradesh 3 0 0.00 1 33.33 2 0 0 NaN 0.00
Dadra and Nagar Haveli and Daman and Diu 2 0 0.00 1 50.00 1 0 0 NaN 0.00
Mizoram 1 0 0.00 1 100.00 0 0 0 NaN 0.00
Sikkim 1 0 0.00 0 0.00 1 0 0 NaN 0.00
Lakshadweep 0 0 NaN 0 NaN 0 0 0 NaN NaN

In Depth Italy Stats (Region Wise Figures)

Confirmed Cases and Deaths- Regions of Italy (With Fatality and Confirmation Rates)

Region Swabs Confirmations NewConfirmations CasesPercentIncrease ConfirmationRate HospitalizedWithSymptoms IntensiveCare ActiveCases Deceased FatalityRate
Lombardia 727146 88537 354 0.40 12.18 3552 173 22683 16012 18.09
Piemonte 309497 30501 56 0.18 9.86 1029 61 5658 3851 12.63
Emilia-Romagna 316909 27739 38 0.14 8.75 429 76 3564 4102 14.79
Veneto 645049 19134 9 0.05 2.97 137 7 1849 1906 9.96
Toscana 246052 10088 2 0.02 4.10 111 31 1255 1031 10.22
Liguria 102173 9619 14 0.15 9.41 192 13 994 1452 15.10
Lazio 249267 7709 16 0.21 3.09 817 59 3163 721 9.35
Marche 101389 6723 4 0.06 6.63 69 9 1352 986 14.67
Campania 193669 4787 10 0.21 2.47 236 7 986 411 8.59
Puglia 114588 4482 1 0.02 3.91 158 12 1283 500 11.16
P.A. Trento 84805 4428 3 0.07 5.22 16 3 410 462 10.43
Sicilia 145979 3440 2 0.06 2.36 67 7 1137 272 7.91
Friuli Venezia Giulia 130838 3267 5 0.15 2.50 45 2 323 333 10.19
Abruzzo 73301 3237 0 0.00 4.42 122 3 770 404 12.48
P.A. Bolzano 64105 2595 0 0.00 4.05 17 5 154 291 11.21
Umbria 68773 1431 0 0.00 2.08 15 2 31 76 5.31
Sardegna 55831 1356 1 0.07 2.43 37 2 190 130 9.59
Valle d’Aosta 14759 1182 0 0.00 8.01 12 0 19 143 12.10
Calabria 68131 1158 0 0.00 1.70 25 1 159 97 8.38
Molise 14109 436 1 0.23 3.09 3 2 162 22 5.05
Basilicata 28909 399 0 0.00 1.38 5 0 33 27 6.77

In Depth Canada Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of Canada (With Fatality Rates)

Province Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
Quebec 50232 521 1.05 4363 60 1.39 8.69 5883.57 511.03 1 in 170
Ontario 28700 380 1.34 2313 21 0.92 8.06 1950.81 157.22 1 in 513
Alberta 6979 24 0.35 143 0 0.00 2.05 1581.41 32.40 1 in 632
British Columbia 2562 4 0.16 164 0 0.00 6.40 501.28 32.09 1 in 1995
Nova Scotia 1055 0 0.00 59 0 0.00 5.59 1079.33 60.36 1 in 926
Saskatchewan 641 2 0.31 10 0 0.00 1.56 542.45 8.46 1 in 1843
Manitoba 294 0 0.00 7 0 0.00 2.38 213.43 5.08 1 in 4685
Newfoundland and Labrador 261 0 0.00 3 0 0.00 1.15 500.61 5.75 1 in 1998
New Brunswick 128 2 1.59 0 0 NaN 0.00 164.10 0.00 1 in 6094
Prince Edward Island 27 0 0.00 0 0 NaN 0.00 170.72 0.00 1 in 5858
Yukon 11 0 0.00 0 0 NaN 0.00 267.78 0.00 1 in 3734
Northwest Territories 5 0 0.00 0 0 NaN 0.00 111.35 0.00 1 in 8981

In Depth China Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of China (With Fatality Rates)

Province Confirmed Deaths FatalityRate
Hubei 68135 4512 6.62
Guangdong 1593 8 0.50
Henan 1276 22 1.72
Zhejiang 1268 1 0.08
Hong Kong 1079 4 0.37
Hunan 1019 4 0.39
Anhui 991 6 0.61
Heilongjiang 945 13 1.38
Jiangxi 937 1 0.11
Shandong 790 7 0.89
Shanghai 672 7 1.04
Jiangsu 653 0 0.00
Beijing 593 9 1.52
Chongqing 579 6 1.04
Sichuan 564 3 0.53
Fujian 358 1 0.28
Hebei 328 6 1.83
Shaanxi 308 3 0.97
Guangxi 254 2 0.79
Inner Mongolia 232 1 0.43
Shanxi 198 0 0.00
Tianjin 192 3 1.56
Yunnan 185 2 1.08
Hainan 169 6 3.55
Jilin 155 2 1.29
Liaoning 149 2 1.34
Guizhou 147 2 1.36
Gansu 139 2 1.44
Xinjiang 76 3 3.95
Ningxia 75 0 0.00
Macau 45 0 0.00
Qinghai 18 0 0.00
Tibet 1 0 0.00

Time Series Curves (Top 20 Countries with the Highest Cases)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most confirmed COVID-19 cases as of today in decreasing order of confirmations.

Confirmed Cases Count (Linear)

Country Wise Time Series Curve

Confirmed Cases Count (Logarithmic)

Country Wise Time Series Curve

Time Series Curves (Top 20 Countries with the Highest Deaths)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most COVID-19 deaths as of today in decreasing order of confirmations.

Death Count (Linear)

Country Wise Time Series Curve

Death Count (Logarithmic)

Country Wise Time Series Curve

Epidemic Curve: Delta in the past 24 hrs (Top 20 Countries with the Highest Cases)

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various countries. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 countries in the world as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Delta in Confirmed Cases

Number of New Cases in the past 24 hrs

Delta in Deaths

Number of Deaths in the past 24 hrs

Measuring Outbreak Velocity: 5 Day Lagging Average Doubling Time (Top 20 Countries with the Highest Cases)

The velocity of an outbreak is determined by a construct known as doubling time. This value describes the number of days, on average, required for the number of cases to double in a given area. For our analysis we use average doubling time, which can be defined as the number of days, on average, required for the average number of COVID-19 cases to double in a given area.

This measure can describe COVID-19 behavior worldwide, in a country, or even in a smaller region such as a state. For our analysis, we will discuss average doubling time at a national level for the top 20 most affected countries.

Below, we have calculated average doubling time for several nations, on a trailing, rolling 5-day basisbased on today’s case values. A decline in average doubling time indicates that the COVID-19 outbreak (confirmation rate) is accelerating (average cases double in fewer days), while an increase of average doubling time indicates that the outbreak is slowing.

Ideally, when social distancing and lockdowns are implemented aggressively in a country and after some period of delay, doubling times should begin to increase in a matter of days, weeks, or months, depending upon the severity of the epidemic and the degree of social distancing achievable.

Given the fact that many countries across the world have already enacted or implemented social distancing measures, this is why one should be cautious not to extrapolate COVID-19 growth rates from trailing statistics.

5 Day Lagging Avg Doubling Time of Confirmations

Confirmed Cases and Deaths Per Million Population and Infection Odds

This metric confirmed cases per million population and deaths per million population shows the extent to which the disease has spread with respect to the population of the country. The metric Infection Odds shows 1 in how many people are infected with COVID-19 in the corresponding country.

For the top 20 countries with most confirmed cases excluding cruise ships

Country_Region ConfirmedCasesPerMillionPopl DeathsPerMillionPopl InfectionOdds
US 5336.24 314.21 1 in 187
Brazil 2222.48 133.20 1 in 450
Russia 2682.51 30.27 1 in 373
United Kingdom 4103.06 575.60 1 in 244
Spain 5112.82 581.25 1 in 196
Italy 3840.08 549.42 1 in 260
France 2790.31 428.68 1 in 358
Germany 2209.47 102.72 1 in 453
India 129.57 3.72 1 in 7718
Turkey 2006.19 55.55 1 in 498
Iran 1807.15 94.59 1 in 553
Peru 4407.18 127.42 1 in 227
Canada 2418.44 187.90 1 in 413
Chile 5021.50 52.30 1 in 199
Mexico 655.01 72.87 1 in 1527
China 60.69 3.35 1 in 16476
Saudi Arabia 2482.27 13.90 1 in 403
Pakistan 325.02 6.69 1 in 3077
Belgium 5093.07 827.19 1 in 196
Qatar 20048.12 13.64 1 in 50

US Detailed State and County Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the state/ county level in USA.

Epidemic Curve: Delta in Confirmed Cases in US States

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various US states. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 states in USA as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in US States

Number of Deaths in the past 24 hrs

Top 50 US Counties with the Highest Cases and Deaths

All NYC boroughs are mentioned together as New York County

County State Confirmations Deaths FatalityRate
New York New York 201999 21477 10.63
Cook Illinois 76266 3570 4.68
Los Angeles California 51678 2294 4.44
Nassau New York 40226 2118 5.27
Suffolk New York 39445 1879 4.76
Westchester New York 33349 1359 4.08
Philadelphia Pennsylvania 22405 1300 5.80
Middlesex Massachusetts 20972 1583 7.55
Wayne Michigan 20227 2425 11.99
Hudson New Jersey 18919 1168 6.17
Bergen New Jersey 18223 1567 8.60
Suffolk Massachusetts 17786 861 4.84
Miami-Dade Florida 17641 685 3.88
Essex New Jersey 17561 1647 9.38
Passaic New Jersey 16045 917 5.72
Middlesex New Jersey 15734 972 6.18
Union New Jersey 15610 1060 6.79
Fairfield Connecticut 15409 1257 8.16
Prince George’s Maryland 14773 530 3.59
Essex Massachusetts 13994 906 6.47
Rockland New York 13100 631 4.82
Harris Texas 12009 228 1.90
New Haven Connecticut 11241 957 8.51
Providence Rhode Island 11052 0 0.00
Montgomery Maryland 11035 595 5.39
Worcester Massachusetts 10816 746 6.90
Fairfax Virginia 10738 378 3.52
Orange New York 10361 444 4.29
Hartford Connecticut 10146 1222 12.04
Dallas Texas 9787 223 2.28
Marion Indiana 9616 571 5.94
Maricopa Arizona 9112 419 4.60
Ocean New Jersey 8627 721 8.36
District of Columbia District of Columbia 8538 460 5.39
Oakland Michigan 8311 975 11.73
Monmouth New Jersey 8100 587 7.25
Lake Illinois 8063 287 3.56
Norfolk Massachusetts 7959 811 10.19
King Washington 7949 564 7.10
Hennepin Minnesota 7932 593 7.48
Plymouth Massachusetts 7766 542 6.98
DuPage Illinois 7543 362 4.80
Riverside California 7486 323 4.31
Milwaukee Wisconsin 7429 294 3.96
Jefferson Louisiana 7424 446 6.01
San Diego California 7100 260 3.66
Orleans Louisiana 7067 505 7.15
Broward Florida 6975 308 4.42
Bristol Massachusetts 6930 404 5.83
Montgomery Pennsylvania 6906 674 9.76

Overall US Choropleth Map

Choropleths are an ideal way to visualize the past/ current COVID-19 hotspots within a country. The below are the hotspots in the US.

County level COVID-19 Confirmations Map

Canada Detailed Province Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the province level in Canada.

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in the most affected Canadian provinces- Quebec, Ontario, Alberta and British Columbia. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Epidemic Curve: Delta in Confirmed Cases in Canadian Provinces

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in Canadian Provinces

Number of Deaths in the past 24 hrs

Data Sources

CSSEGISandData, The NY Times, amodm/api-covid19-in and pcm-dpc